Integrating RapidAI in an Evolving Hub and Spoke Center

Introduction/Background: As the rapid assessment of suspected stroke patients is imperative to reduce death and disability, rapid and reliable imaging studies are required to guide treatment decisions for thrombolytic therapies and thrombectomy. The integration of Artificial intelligence (AI) imaging platforms within acute stroke assessment has been shown to improve treatment times with the overall goal of improving outcomes. The process of adoption of this technology has not been well described. We sought to describe a process of adopting one AI imaging platform, RapidAI, within a hub and spoke health care system in the mid-south United States. Methods: Using a process improvement model which identified the need for more convenient and rapid interpretation of imaging, we sought to identify the specific steps of technology adoption, ensuring success in the transition to RapidAI to support faster interpretation times among multiple members of the acute stroke team. Results: Because of strong leadership at the system level, our organization has been able to incorporate RapidAI in all spoke centers for the acute evaluation and treatment of stroke patients. Conclusions: AI imaging platforms, such as RapidAI, can be incorporated within hub and spoke systems of care through strong system leadership and distinct steps. These steps could also be considered for stand-alone facilities with the creation of strong partnerships in the treatment of acute stroke patients.